Distributed resource allocation and load management for smart grid-powered edge computing systems

Xiaojing Chen; Hanfei Wen; Wei Ni; Shunqing Zhang; Xin Wang; Shugong Xu

doi:10.1109/ICCC52777.2021.9580406

Distributed resource allocation and load management for smart grid-powered edge computing systems

Xiaojing Chen
, Hanfei Wen
, Wei Ni
, Shunqing Zhang
, Xin Wang
, Shugong Xu

Shanghai University
CSIRO
Fudan University

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

1 Citation (Scopus)

Abstract

In this paper, we propose distributed online resource allocation and load management (DORL) for smart grid-powered edge computing (EC) systems. Taking into account renewable energy, two-way energy trading, and dynamic energy pricing, the resource allocation and load management task is formulated as an infinite-horizon optimization problem, which minimizes jointly the energy transaction cost of the base station (BS) and the energy consumption of the Internet-of- Things (IoT) devices. Building on the stochastic dual-subgradient method, the proposed DORL algorithm decouples the real-time decisions of the BS and devices, and stabilizes the backlogs of computation tasks with a cost-backlog tradeoff of $[\eta, \frac{1}{\eta}]$, for any $\eta > 0$. Theoretical analyses prove that the proposed DORL can yield a feasible and asymptotically optimal solution.

Original language	English
Title of host publication	2021 IEEE/CIC International Conference on Communications in China, ICCC 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	266-271
Number of pages	6
ISBN (Electronic)	9781665443852
DOIs	https://doi.org/10.1109/ICCC52777.2021.9580406
Publication status	Published - 28 Jul 2021
Externally published	Yes
Event	2021 IEEE/CIC International Conference on Communications in China, ICCC 2021 - Xiamen, China Duration: 28 Jul 2021 → 30 Jul 2021

Publication series

Name	2021 IEEE/CIC International Conference on Communications in China, ICCC 2021

Conference

Conference	2021 IEEE/CIC International Conference on Communications in China, ICCC 2021
Country/Territory	China
City	Xiamen
Period	28/07/21 → 30/07/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Edge computing
Load management
Resource allocation
Smart grid
Stochastic approximation

Access to Document

10.1109/ICCC52777.2021.9580406

Cite this

Chen, X., Wen, H., Ni, W., Zhang, S., Wang, X., & Xu, S. (2021). Distributed resource allocation and load management for smart grid-powered edge computing systems. In 2021 IEEE/CIC International Conference on Communications in China, ICCC 2021 (pp. 266-271). (2021 IEEE/CIC International Conference on Communications in China, ICCC 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCC52777.2021.9580406

Chen, Xiaojing ; Wen, Hanfei ; Ni, Wei et al. / Distributed resource allocation and load management for smart grid-powered edge computing systems. 2021 IEEE/CIC International Conference on Communications in China, ICCC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 266-271 (2021 IEEE/CIC International Conference on Communications in China, ICCC 2021).

@inproceedings{3b70ba22a9904f74b8c614457cd6ce96,

title = "Distributed resource allocation and load management for smart grid-powered edge computing systems",

abstract = "In this paper, we propose distributed online resource allocation and load management (DORL) for smart grid-powered edge computing (EC) systems. Taking into account renewable energy, two-way energy trading, and dynamic energy pricing, the resource allocation and load management task is formulated as an infinite-horizon optimization problem, which minimizes jointly the energy transaction cost of the base station (BS) and the energy consumption of the Internet-of- Things (IoT) devices. Building on the stochastic dual-subgradient method, the proposed DORL algorithm decouples the real-time decisions of the BS and devices, and stabilizes the backlogs of computation tasks with a cost-backlog tradeoff of \$[\textbackslash{}eta, \textbackslash{}frac\{1\}\{\textbackslash{}eta\}]\$, for any \$\textbackslash{}eta > 0\$. Theoretical analyses prove that the proposed DORL can yield a feasible and asymptotically optimal solution.",

keywords = "Edge computing, Load management, Resource allocation, Smart grid, Stochastic approximation",

author = "Xiaojing Chen and Hanfei Wen and Wei Ni and Shunqing Zhang and Xin Wang and Shugong Xu",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE/CIC International Conference on Communications in China, ICCC 2021 ; Conference date: 28-07-2021 Through 30-07-2021",

year = "2021",

month = jul,

day = "28",

doi = "10.1109/ICCC52777.2021.9580406",

language = "English",

series = "2021 IEEE/CIC International Conference on Communications in China, ICCC 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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}

Chen, X, Wen, H, Ni, W, Zhang, S, Wang, X & Xu, S 2021, Distributed resource allocation and load management for smart grid-powered edge computing systems. in 2021 IEEE/CIC International Conference on Communications in China, ICCC 2021. 2021 IEEE/CIC International Conference on Communications in China, ICCC 2021, Institute of Electrical and Electronics Engineers Inc., pp. 266-271, 2021 IEEE/CIC International Conference on Communications in China, ICCC 2021, Xiamen, China, 28/07/21. https://doi.org/10.1109/ICCC52777.2021.9580406

Distributed resource allocation and load management for smart grid-powered edge computing systems. / Chen, Xiaojing; Wen, Hanfei; Ni, Wei et al.
2021 IEEE/CIC International Conference on Communications in China, ICCC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 266-271 (2021 IEEE/CIC International Conference on Communications in China, ICCC 2021).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - Distributed resource allocation and load management for smart grid-powered edge computing systems

AU - Chen, Xiaojing

AU - Wen, Hanfei

AU - Ni, Wei

AU - Zhang, Shunqing

AU - Wang, Xin

AU - Xu, Shugong

PY - 2021/7/28

Y1 - 2021/7/28

N2 - In this paper, we propose distributed online resource allocation and load management (DORL) for smart grid-powered edge computing (EC) systems. Taking into account renewable energy, two-way energy trading, and dynamic energy pricing, the resource allocation and load management task is formulated as an infinite-horizon optimization problem, which minimizes jointly the energy transaction cost of the base station (BS) and the energy consumption of the Internet-of- Things (IoT) devices. Building on the stochastic dual-subgradient method, the proposed DORL algorithm decouples the real-time decisions of the BS and devices, and stabilizes the backlogs of computation tasks with a cost-backlog tradeoff of $[\eta, \frac{1}{\eta}]$, for any $\eta > 0$. Theoretical analyses prove that the proposed DORL can yield a feasible and asymptotically optimal solution.

AB - In this paper, we propose distributed online resource allocation and load management (DORL) for smart grid-powered edge computing (EC) systems. Taking into account renewable energy, two-way energy trading, and dynamic energy pricing, the resource allocation and load management task is formulated as an infinite-horizon optimization problem, which minimizes jointly the energy transaction cost of the base station (BS) and the energy consumption of the Internet-of- Things (IoT) devices. Building on the stochastic dual-subgradient method, the proposed DORL algorithm decouples the real-time decisions of the BS and devices, and stabilizes the backlogs of computation tasks with a cost-backlog tradeoff of $[\eta, \frac{1}{\eta}]$, for any $\eta > 0$. Theoretical analyses prove that the proposed DORL can yield a feasible and asymptotically optimal solution.

KW - Edge computing

KW - Load management

KW - Resource allocation

KW - Smart grid

KW - Stochastic approximation

UR - https://www.scopus.com/pages/publications/85119352982

U2 - 10.1109/ICCC52777.2021.9580406

DO - 10.1109/ICCC52777.2021.9580406

M3 - Conference Proceeding

AN - SCOPUS:85119352982

T3 - 2021 IEEE/CIC International Conference on Communications in China, ICCC 2021

SP - 266

EP - 271

BT - 2021 IEEE/CIC International Conference on Communications in China, ICCC 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2021 IEEE/CIC International Conference on Communications in China, ICCC 2021

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ER -

Chen X, Wen H, Ni W, Zhang S, Wang X, Xu S. Distributed resource allocation and load management for smart grid-powered edge computing systems. In 2021 IEEE/CIC International Conference on Communications in China, ICCC 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 266-271. (2021 IEEE/CIC International Conference on Communications in China, ICCC 2021). doi: 10.1109/ICCC52777.2021.9580406

Distributed resource allocation and load management for smart grid-powered edge computing systems

Abstract

Publication series

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UN SDGs

Keywords

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